Decoding corporate communication strategies: Analysing mandatory published information under Pillar 3 across turbulent periods with unsupervised machine learning - Anna Pilková; Michal Munk; Lívia Kelebercová (PLoS ONE, 2025)
This study explores the communication patterns of Slovak banks with stakeholders through mandatory disclosures mandated by Basel III’s Pillar 3 framework and annual reports in 2007−2022. Our primary objective is to identify key topics communicated by banks and analysing the sentiment of this communication during turbulent periods (i.e., alternating periods of stability and crisis) in 2007−2022. Textual data was collected from Pillar 3 disclosures, annual reports, and additional regulatory reports. A hybrid model was developed to extract the most important keywords from each collected document chapter. This hybrid model (model combining multiple approaches) combines elements of statistical approaches to keyword extraction, (keyword frequency dictionary), linguistic approaches (pair-of-speech tagging in order to select noun-phrases), and machine-learning based approaches (BERT) to extract meaningful keywords. Subsequently, a sentiment analysis was performed on the extracted keywords using a Loughran-McDonald lexicon (list of words labelled with sentiment) specially designed for financial texts. Based on the adjusted univariate results, we can reject the global null hypothesis of independence of the sentiment category of keywords from time for negative sentiment at p = 0.0000 for positive sentiment at p = 0.0005, and for neutral sentiment at p = 0.0000 significant level. The multilevel comparison revealed that negative sentiment was most frequent during the global financial crisis and the COVID-19 pandemic, likely impacting stakeholder confidence and trust. Conversely, positive sentiment dominated during periods of financial stability, potentially enhancing stakeholder satisfaction and investment decisions. This research points out that the sentiment of the selected commercial bank documents changes depending on the years. A commercial bank can use this knowledge and include sentiment information as predictors when modelling financial distress. For bank management of selected commercial bank the examined documents are an important communication tool, the wording of which can have a significant impact on stakeholder behaviour towards the bank, their styling is very important.